What is the ‘Diabetes Data Science Catalyst’?
The Diabetes Data Science Catalyst will support research of relevance to both diabetes and cardiovascular diseases through the use of health data science and advanced analytics such as Artificial Intelligence.
Professor Ewan Pearson is the Theme Lead for the Diabetes Data Science Catalyst.
Why is the ‘Diabetes Data Science Catalyst’ important for cardiovascular research?
Cardiovascular diseases and diabetes are closely related – cardiovascular diseases are the cause of death in around two thirds of people with diabetes. However, there remain many unanswered research questions about the links between diabetes and cardiovascular diseases and how best to target treatments to help patients and their families living with these conditions.
What are we doing?
We are:
- Supporting driver projects that speed up the use of health data in diabetes research.
- Supporting and enabling researchers to better understand and use healthcare systems data. We held a showcase event to highlight the support available. Work is also ongoing to develop and share Diabetes Phenotypes. You can read about this in our Computable Phenotypes area here.
- Providing guidance for researchers wishing to use diabetes datasets for research. Have a look at the information we have collated on key national datasets and how to access them:
How to access data & other considerations
The guidance currently refers to clinical trials, although many of these datasets are accessible within Trusted Research Environments under CVD-COVID-UK/COVID-IMPACT.
Extending the research potential of diabetes cohorts, Diabetes Cohorts will be some of the first cohorts to join our new platform.
Diabetes Community of Practice
Diabetes Community of Practice will bring together researchers working within diabetes health data research across the UK providing the opportunity for group members to present their latest research findings and make new connections and collaborative links. Meetings will be held quarterly.
If you’d like to be part of the Diabetes Community of Practice, please email bhfdsc@hdruk.ac.uk.
Areas of work
Find out more about our data-led research.
Whole Population Data
Better use of nationally-collated, structured, coded data: accessing, improving and using linked, national, population-wide health data.
Defining Disease
Developing methods to define cardiovascular health and disease in computable form through a collaborative network of expertise that provides a world-leading, open, cardiovascular phenotype library of tools and protocols.
Enhancing Cohorts
Facilitating the linkage of large, ‘omics-rich’ cohorts to electronic health records to better understand the causes of cardiovascular diseases.
Data Enabled Clinical Trials
Supporting the development of efficient, cost-effective trials, using routine health data to recruit and follow patients with cardiovascular conditions.
Imaging
Better use of unstructured data: addressing the challenges of accessing, improving and using unstructured data, for example from cardiac and brain imaging, medical free text and electrocardiograms.
Smartphones and Wearables
Exploring how data from apps and wearables, linked to other health datasets, can inform trajectories of cardiovascular health and disease.
CVD-COVID-UK / COVID-IMPACT
One of seven National Flagship Projects approved by the NIHR-BHF Cardiovascular Partnership, linking population healthcare datasets across the UK to understand the relationship between COVID-19 and cardiovascular diseases.
Stroke Data Science Catalyst
This partnership between the BHF Data Science Centre, HDR UK and the Stroke Association will enable researchers to securely access, link and analyse existing UK health data, speeding up the search for better stroke prevention, treatments and care.
Kidney Data Science Catalyst
This partnership between the BHF Data Science Centre, Kidney Research UK and HDR UK will enable researchers to securely access, link and analyse existing UK health data, speeding up the search for better kidney and cardiovascular disease prevention, treatments, and care.